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my-project-public — gitlawb

#1	from agents import Agent, Runner, enable_verbose_stdout_logging, function_tool
#2	from dotenv import load_dotenv
#3
#4	from mem0 import MemoryClient
#5
#6	enable_verbose_stdout_logging()
#7
#8	load_dotenv()
#9
#10	# Initialize Mem0 client
#11	mem0 = MemoryClient()
#12
#13
#14	# Define memory tools for the agent
#15	@function_tool
#16	def search_memory(query: str, user_id: str) -> str:
#17	"""Search through past conversations and memories"""
#18	memories = mem0.search(query, user_id=user_id, limit=3)
#19	if memories:
#20	return "\n".join([f"- {mem['memory']}" for mem in memories])
#21	return "No relevant memories found."
#22
#23
#24	@function_tool
#25	def save_memory(content: str, user_id: str) -> str:
#26	"""Save important information to memory"""
#27	mem0.add([{"role": "user", "content": content}], user_id=user_id)
#28	return "Information saved to memory."
#29
#30
#31	# Specialized agents
#32	travel_agent = Agent(
#33	name="Travel Planner",
#34	instructions="""You are a travel planning specialist. Use get_user_context to
#35	understand the user's travel preferences and history before making recommendations.
#36	After providing your response, use store_conversation to save important details.""",
#37	tools=[search_memory, save_memory],
#38	model="gpt-4.1-nano-2025-04-14",
#39	)
#40
#41	health_agent = Agent(
#42	name="Health Advisor",
#43	instructions="""You are a health and wellness advisor. Use get_user_context to
#44	understand the user's health goals and dietary preferences.
#45	After providing advice, use store_conversation to save relevant information.""",
#46	tools=[search_memory, save_memory],
#47	model="gpt-4.1-nano-2025-04-14",
#48	)
#49
#50	# Triage agent with handoffs
#51	triage_agent = Agent(
#52	name="Personal Assistant",
#53	instructions="""You are a helpful personal assistant that routes requests to specialists.
#54	For travel-related questions (trips, hotels, flights, destinations), hand off to Travel Planner.
#55	For health-related questions (fitness, diet, wellness, exercise), hand off to Health Advisor.
#56	For general questions, you can handle them directly using available tools.""",
#57	handoffs=[travel_agent, health_agent],
#58	model="gpt-4.1-nano-2025-04-14",
#59	)
#60
#61
#62	def chat_with_handoffs(user_input: str, user_id: str) -> str:
#63	"""
#64	Handle user input with automatic agent handoffs and memory integration.
#65
#66	Args:
#67	user_input: The user's message
#68	user_id: Unique identifier for the user
#69
#70	Returns:
#71	The agent's response
#72	"""
#73	# Run the triage agent (it will automatically handoffs when needed)
#74	result = Runner.run_sync(triage_agent, user_input)
#75
#76	# Store the original conversation in memory
#77	conversation = [{"role": "user", "content": user_input}, {"role": "assistant", "content": result.final_output}]
#78	mem0.add(conversation, user_id=user_id)
#79
#80	return result.final_output
#81
#82
#83	# Example usage
#84	# response = chat_with_handoffs("Which places should I vist?", user_id="alex")
#85	# print(response)
#86

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